Ecological resilience in lakes and the conjunction fallacy

Early warning indicators capture catastrophic transitions driven by explicit rates of environmental change

In response to external changes, ecosystems can undergo catastrophic transitions. Early warning indicators aim to predict such transitions based on the phenomenon of critical slowing down at bifurcation points found under a constant environment. When an explicit rate of environmental change is considered, catastrophic transitions can become distinct phenomena from bifurcations, and result from a delayed response to noncatastrophic bifurcations. We use a trophic metacommunity model where transitions in time series and bifurcations of the system are distinct phenomena. We calculate early warning indicators from the time series of the continually changing system and show that they predict not the bifurcation of the underlying system but the actual catastrophic transition driven by the explicit rate of change. Predictions based on the bifurcation structure could miss catastrophic transitions that can still be captured by early warning signals calculated from time series. Our results expand the repertoire of mechanistic models used to anticipate catastrophic transitions to nonequilibrium ecological systems exposed to a constant rate of environmental change.

Early warning signals have limited applicability to empirical lake data

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.

Bimodality and alternative equilibria do not help explain long-term patterns in shallow lake chlorophyll-a

Since its inception, the theory of alternative equilibria in shallow lakes has evolved and been applied to an ever wider range of ecological and socioecological systems. The theory posits the existence of two alternative stable states or equilibria, which in shallow lakes are characterised by either clear water with abundant plants or turbid water where phytoplankton dominate. Here, we used data simulations and real-world data sets from Denmark and north-eastern USA (902 lakes in total) to examine the relationship between shallow lake phytoplankton biomass (chlorophyll-a) and nutrient concentrations across a range of timescales. The data simulations demonstrated that three diagnostic tests could reliably identify the presence or absence of alternative equilibria. The real-world data accorded with data simulations where alternative equilibria were absent. Crucially, it was only as the temporal scale of observation increased (>3 years) that a predictable linear relationship between nutrient concentration and chlorophyll-a was evident. Thus, when a longer term perspective is taken, the notion of alternative equilibria is not required to explain the response of chlorophyll-a to nutrient enrichment which questions the utility of the theory for explaining shallow lake response to, and recovery from, eutrophication.

Impact of submerged macrophytes on growth and 2-MIB release risk of Pseudanabaena sp.: From field monitoringa to cultural experiments

The off-flavor compound 2-methylisoborneol (2-MIB) is generally associated with the proliferation and metabolism of filamentous cyanobacteria in shallow freshwater ecosystems. Here field monitoring in East Taihu Lake from July to October 2021, along with cultural experiments, was conducted to determine the impact of submerged macrophytes on the growth and 2-MIB production of filamentous cyanobacteria. Pseudanabaena sp. was identified as the 2-MIB producer with the highest detection rate (100%) and correlation coefficient (R=0.68, p < 0.001). The 2-MIB concentration and algal growth in the macrophyte-dominated zones were markedly decreased compared with those in the phytoplankton-dominated zone. Five submerged macrophytes classified into flat-leaf type (Vallisneria natans and Potamogeton crispus) and thin-leaf type (Hydrilla verticillata, Ceratophyllum demersum, and Myriophyllum spicatum) exhibited strong inhibition effects against Pseudanabaena sp.: Overall inhibition efficiencies (IEs) of 92.7% ± 6.8% and 92.7% ± 8.4% for cell growth and 2-MIB production were achieved, respectively. Moreover, the thin-leaf macrophytes exhibited significant higher IEs for cell growth (94.0% vs. 84.7%) and 2-MIB production (99.4% vs. 82.6%) than the flat-leaf macrophytes and can be selected as pioneer species in controlling odor problems. Nutrient uptake, increasing water clarity, shading effects, and allelopathic effects of the submerged macrophytes were found to be the dominant inhibition mechanisms.

Landscape determinants of pelagic and benthic primary production in northern lakes

Global change affects gross primary production (GPP) in benthic and pelagic habitats of northern lakes by influencing catchment characteristics and lake water biogeochemistry. However, how changes in key environmental drivers manifest and impact total (i.e., benthic + pelagic) GPP and the partitioning of total GPP between habitats represented by the benthic share (autotrophic structuring) is unclear. Using a dataset from 26 shallow lakes located across Arctic, subarctic, and boreal northern Sweden, we investigate how catchment properties (air temperature, land cover, hydrology) affect lake physico-chemistry and patterns of total GPP and autotrophic structuring. We find that total GPP was mostly light limited, due to high dissolved organic carbon (DOC) concentrations originating from catchment soils with coniferous vegetation and wetlands, which is further promoted by high catchment runoff. In contrast, autotrophic structuring related mostly to the relative size of the benthic habitat, and was potentially modified by CO₂ fertilization in the subarctic, resulting in significantly higher total GPP relative to the other biomes. Across Arctic and subarctic sites, DIC and CO₂ were unrelated to DOC, indicating that external inputs of inorganic carbon can influence lake productivity patterns independent of terrestrial DOC supply. By comparison, DOC and CO₂ were correlated across boreal lakes, suggesting that DOC mineralization acts as an important CO₂ source for these sites. Our results underline that GPP as a resource is regulated by landscape properties, and is sensitive to large-scale global changes (warming, hydrological intensification, recovery of acidification) that promote changes in catchment characteristics and aquatic physico-chemistry. Our findings aid in predicting global change impacts on autotrophic structuring, and thus community structure and resource use of aquatic consumers in general. Given the similarities of global changes across the Northern hemisphere, our findings are likely relevant for northern lakes globally.

Effects of climate change and anthropogenic activities on lake environmental dynamics: A case study in Lake Bosten Catchment, NW China

Arid and semiarid regions account for ∼ 40% of the world's land area. Rivers and lakes in these regions provide sparse, but valuable, water resources for the fragile environments, and play a vital role in the development and sustainability of local societies. During the late 1980s, the climate of arid and semiarid northwest China dramatically changed from "warm-dry" to "warm-wet". Understanding how these environmental changes and anthropogenic activities affect water quantity and quality is critically important for protecting aquatic ecosystems and determining the best use of freshwater resources. Lake Bosten is the largest inland freshwater lake in NW China and has experienced inter-conversion between freshwater and brackish status. Herein, we explored the long-term water level and salinity trends in Lake Bosten from 1958 to 2019. During the past 62 years, the water level and salinity of Lake Bosten exhibited inverse "W-shaped" and "M-shaped" patterns, respectively. Partial least squares path modeling (PLS-PM) suggested that the decreasing water level and salinization during 1958-1986 were mainly caused by anthropogenic activities, while the variations in water level and salinity during 1987-2019 were mainly affected by climate change. The transformation of anthropogenic activities and climate change is beneficial for sustainable freshwater management in the Lake Bosten Catchment. Our findings highlight the benefit of monitoring aquatic environmental changes in arid and semi-arid regions over the long-term for the purpose of fostering a balance between socioeconomic development and ecological protection of the lake environment.

Applying early warning indicators to predict critical transitions in a lake undergoing multiple changes

Lakes are dynamic ecosystems that can transition among stable states. Since ecosystem-scale transitions can be detrimental and difficult to reverse, being able to predict impending critical transitions in state variables has become a major area of research. However, not all transitions are detrimental, and there is considerable interest in better evaluating the success of management interventions to support adaptive management strategies. Here, we retrospectively evaluated the agreement between time series statistics (i.e., standard deviation, autocorrelation, skewness, and kurtosis-also known as early warning indicators) and breakpoints in state variables in a lake (Lake Simcoe, Ontario, Canada) that has improved from a state of eutrophication. Long-term (1980 to 2019) monitoring data collected fortnightly throughout the ice-free season were used to evaluate historical changes in 15 state variables (e.g., dissolved organic carbon, phosphorus, chlorophyll a) and multivariate-derived time series at three monitoring stations (shallow, middepth, deep) in Lake Simcoe. Time series results from the two deep-water stations indicate that over this period Lake Simcoe transitioned from an algal-dominated state toward a state with increased water clarity (i.e., Secchi disk depth) and silica and lower nutrient and chlorophyll a concentrations, which coincided with both substantial management intervention and the establishment of invasive species (e.g., Dreissenid mussels). Consistent with improvement, Secchi depth at the deep-water stations demonstrated expected trends in statistical indicators prior to identified breakpoints, whereas total phosphorus and chlorophyll a revealed more nuanced patterns. Overall, state variables were largely found to yield inconsistent trends in statistical indicators, so many breakpoints were likely not reflective of traditional bifurcation critical transitions. Nevertheless, statistical indicators of state variable time series may be a valuable tool for the adaptive management and long-term monitoring of lake ecosystems, but we call for more research within the domain of early warning indicators to establish a better understanding of state variable behavior prior to lake changes.

Regime shifts, trends, and variability of lake productivity at a global scale

Lakes can change dramatically following a slow change in conditions. They can abruptly shift from being oligotrophic to eutrophic or vice versa, in what is called a regime shift. Despite the important consequences for ecosystems and human activities of abrupt shifts, we do not know how frequent they are or how they are distributed globally. To answer these questions, we analyze lake productivity dynamics of 1,015 lakes worldwide. Our results show few experienced regime shifts, yet the occurrence of observed regime shifts is increasing over time. Our analysis' global scope allows us to better understand the occurrence of regime shifts and the socioeconomic drivers associated with them. This knowledge will help manage lakes' response to global change.

Lakes are often described as sentinels of global change. Phenomena like lake eutrophication, algal blooms, or reorganization in community composition belong to the most studied ecosystem regime shifts. However, although regime shifts have been well documented in several lakes, a global assessment of the prevalence of regime shifts is still missing, and, more in general, of the factors altering stability in lake status, is missing. Here, we provide a first global assessment of regime shifts and stability in the productivity of 1,015 lakes worldwide using trophic state index (TSI) time series derived from satellite imagery. We find that 12.8% of the lakes studied show regime shifts whose signatures are compatible with tipping points, while the number of detected regime shifts from low to high TSI has increased over time. Although our results suggest an overall stable picture for global lake dynamics, the limited instability signatures do not mean that lakes are insensitive to global change. Modeling the interaction between lake climatic, geophysical, and socioeconomic features and their stability properties, we find that the probability of a lake experiencing a tipping point increases with human population density in its catchment, while it decreases as the gross domestic product of that population increases. Our results show how quantifying lake productivity dynamics at a global scale highlights socioeconomic inequalities in conserving natural environments.

The role of humic substances in sediment phosphorus release in northern lakes

In northern lakes, which are often stained and productive, the impacts of dissolved organic carbon (DOC) on sediment phosphorus (P) release are largely unexplored. Here we elucidated the factors behind experimentally-derived sediment release rates of P by diffusion (DF) in four Finnish lakes with a range of colour. Next, we extended our analysis to a larger set of northern lakes for further insights regarding possible implications of organic substances on sediment P release. The significant correlation between pore-water soluble reactive P and dissolved iron, and a positive effect of iron-bound sedimentary P (Fe-P) on DF supports the classic paradigm of redox-dependent P release in the four Finnish lakes studied. Nevertheless, the P release from Fe-P may be inhibited by humic substances, as we observed lower Fe-P and negative DF in two humic rich lakes (high DOC). The analysis of a larger set of northern lakes supported the negative effect of humic substances on P release rate (RR) determined by in situ P increases. In this dataset, DOC correlated positively with water colour and negatively with RR. Furthermore, multiple stepwise regression analysis selected sediment total P and organic matter content in sediments (LOI) as the best predictors of RR, similar to a previously published model by Nürnberg (1988). While the model predictions (RR_pred) were correlated to RR in the present study, they tended to overestimate RR that was determined in closed experimental systems. The inhibiting effects of humic substances on RR may be manifested in both internal P loading and primary production.

Opportunities for combining data of Estonian and Russian monitoring to reflect on water quality in large transboundary Lake Peipsi

Lake Peipsi, one of the world's largest lakes, is shared between Estonia and Russia. The water quality in different parts of the lake has so far been assessed independently. Here we explore opportunities for combining data of Estonian and Russian monitoring. For that, we 1) analysed the compatibility of data for some water quality variables; 2) estimated the potential effects of the differences in sampling frequency; 3) provided a few regression models to calculate the missing data for months not sampled by the Russian side. Data of the concurrent Estonian and Russian sampling indicated a good compatibility. Estonian data analysis suggested that water quality assessment results are sensitive to sampling frequency. For example, total phosphorus (TP) in the largest basin showed a long-term decreasing trend in three month data that disappeared when data for other months were added. Disregarding some months may lead to under- or overestimation of certain factors with no consistency in the response of different basins. Hence, data of the whole ice-free period are recommended for an adequate water quality assessment. Furthermore, we demonstrated that monthly values of the water quality variables of the same year are autocorrelated. Based on this, we filled the gaps in the long-term data and compiled a dataset for the whole lake that enables its most comprehensive use in water quality assessment and management. Long-term data revealed no water quality improvement of Lake Peipsi. Further reduction of the external nutrient load is needed. Eutrophication is sustained by high internal phosphorus load.

Evaluating the performance of temporal and spatial early warning statistics of algal blooms

Regime shifts have large consequences for ecosystems and the services they provide. However, understanding the potential for, causes of, proximity to, and thresholds for regime shifts in nearly all settings is difficult. Generic statistical indicators of resilience have been proposed and studied in a wide range of ecosystems as a method to detect when regime shifts are becoming more likely without direct knowledge of underlying system dynamics or thresholds. These early warning statistics (EWS) have been studied separately but there have been few examples that directly compare temporal and spatial EWS in ecosystem-scale empirical data. To test these methods, we collected high-frequency time series and high-resolution spatial data during a whole-lake fertilization experiment while also monitoring an adjacent reference lake. We calculated two common EWS, standard deviation and autocorrelation, in both time series and spatial data to evaluate their performance prior to the resulting algal bloom. We also applied the quickest detection method to generate binary alarms of resilience change from temporal EWS. One temporal EWS, rolling window standard deviation, provided advanced warning in most variables prior to the bloom, showing trends and between-lake patterns consistent with theory. In contrast, temporal autocorrelation and both measures of spatial EWS (spatial SD, Moran's  I) provided little or no warning. By compiling time series data from this and past experiments with and without nutrient additions, we were able to evaluate temporal EWS performance for both constant and changing resilience conditions. True positive alarm rates were 2.5-8.3 times higher for rolling window standard deviation when a lake was being pushed towards a bloom than the rate of false positives when it was not. For rolling window autocorrelation, alarm rates were much lower and no variable had a higher true positive than false positive alarm rate. Our findings suggest temporal EWS provide advanced warning of algal blooms and that this approach could help managers prepare for and/or minimize negative bloom impacts.

Bridging Theories for Ecosystem Stability Through Structural Sensitivity Analysis of Ecological Models in Equilibrium

Ecologists are challenged by the need to bridge and synthesize different approaches and theories to obtain a coherent understanding of ecosystems in a changing world. Both food web theory and regime shift theory shine light on mechanisms that confer stability to ecosystems, but from different angles. Empirical food web models are developed to analyze how equilibria in real multi-trophic ecosystems are shaped by species interactions, and often include linear functional response terms for simple estimation of interaction strengths from observations. Models of regime shifts focus on qualitative changes of equilibrium points in a slowly changing environment, and typically include non-linear functional response terms. Currently, it is unclear how the stability of an empirical food web model, expressed as the rate of system recovery after a small perturbation, relates to the vulnerability of the ecosystem to collapse. Here, we conduct structural sensitivity analyses of classical consumer-resource models in equilibrium along an environmental gradient. Specifically, we change non-proportional interaction terms into proportional ones, while maintaining the equilibrium biomass densities and material flux rates, to analyze how alternative model formulations shape the stability properties of the equilibria. The results reveal no consistent relationship between the stability of the original models and the proportionalized versions, even though they describe the same biomass values and material flows. We use these findings to critically discuss whether stability analysis of observed equilibria by empirical food web models can provide insight into regime shift dynamics, and highlight the challenge of bridging alternative modelling approaches in ecology and beyond.

Seasonal Dynamics of Algal Net Primary Production in Response to Phosphorus Input in a Mesotrophic Subtropical Plateau Lake, Southwestern China

A comprehensive 3-dimensional hydrodynamic and eutrophication model, the environmental fluid dynamics code model (EFDC) with three functional phytoplankton groups, was applied to simulate the algal dynamics in a mesotrophic P-limited subtropical plateau lake, Lake Erhai, Southwestern China. Field investigations revealed the seasonal patterns in external total phosphorus (TP) input and TP concentration, as well as the composition of the phytoplankton community. The model was calibrated to reproduce qualitative features and the succession of phytoplankton communities, and the net primary production was calculated. The modeled daily net primary production (NPP) ranged between −16.89 and 15.12 mg C/m2/d and exhibited significant seasonal variation. The competition for phosphorus and temperature was identified as the primary governing factor of NPP by analyzing the parameter sensitivity and limitation factors of the lake. The simulation of four nutrient loading reduction scenarios suggested high phytoplankton biomass and NPP sensitivity to the external TP reduction. A significant positive correlation was found among NPP, total phytoplankton biomass and TP concentration. Overall, this work offers an alternative approach to estimating lake NPP, which has the potential to improve sustainable lake management.

Stoichiometric and physiological mechanisms that link hub traits of submerged macrophytes with ecosystem structure and functioning

Eutrophication strongly influences plant stoichiometric characteristics and physiological status by altering nutrient and light availability in the water column. However, the mechanisms linking plant functional traits with ecosystem structure and functioning to clarify the decline of submerged macrophytes have not been fully elucidated to date. Therefore, based on a field investigation of 26 macrophytic shallow lakes on the Yangtze Plain, we first constructed a plant trait network at the whole-plant level to determine the hub traits of submerged macrophytes that play central regulatory roles in plant phenotype. Our results suggested that organ (leaf, stem, and root) phosphorus (P), starch, and total nonstructural carbohydrate (TNC) contents were hub traits. Organ starch and TNC were consistent with those in the experiment-based network obtained from a three-month manipulation experiment. Next, the mechanisms underlying the relationships between the hub traits and vital aspects of ecological performance were carefully investigated using field investigation data. Specifically, stoichiometric homeostasis of P (H_P), starch, and TNC were positively associated with dominance and biomass at the species level, and community biomass at the community level. Additionally, structural equation modeling clarified not only a hypothesized pathway from eutrophication to water clarity and community TNC, but also combined effects of community TNC and H_P on community biomass. That is, ecosystems dominated by more homeostatic communities tended to have more carbon (C)-rich compounds in relatively oligotrophic conditions, which promoted the primary production of macrophytes. Eutrophication was determined to affect community structure by inhibiting the predominance of more homeostatic species and the production of carbohydrates. Finally, reduced community biomass and increased nutrient contents and nutrient:C ratios in plants induced by eutrophication implied a decrease in the C sink in biomass and may potentially lead to an enhancement of litter decomposition rates and nutrient cycling rates. By adjusting plant responses to eutrophication, stoichiometric and physiological mechanisms linking plant traits with ecosystem structure have important implications for understanding ecosystem processes, and these results may contribute to practical management to achieve the restoration of submerged macrophytes and ecosystem services.

Warming-driven shifts in ecological control of fish communities in a large northern Chinese lake over 66 years

Warming, land-use change, and habitat loss are three major threats to aquatic biodiversity worldwide under the influences of anthropogenic disturbances. Positive feedback between warming and bottom-up regulation may cause irreversible ecological regime shifts. Threshold dynamics of interspecific interactions have been rarely studied in freshwater fish communities using threshold community models. Here we use 66 years (1950-2015) of data to link four ecological regime shifts of 9-species fish communities to climatic and land use changes in Lake Hulun, the largest freshwater lake of Northern China. Overfishing caused the collapse of piscivorous fish populations and an ecological regime shift of Lake Hulun in the late 1950s. The first recorded algal bloom of Lake Hulun took place in 1986, with accelerated warming and rapid increases in livestock grazing. The dominance of planktivorous minnow populations reduced fish biodiversity in a nonlinear, threshold manner when annual mean ambient temperature was >0.12 °C. Multivariate environmental vector regression demonstrated that warming, eutrophication, and water-storage reduction (i.e., habitat loss) were related to three ecological regime shifts of Lake Hulun from 1960 to 2015. Multivariate autoregressive models (MAR) did not detect predation by piscivorous fish in Lake Hulun after 1960. Threshold MAR models indicated that dominant minnow populations and other prey fish populations switched from top-down to bottom-up control during the 1980s. Sustained positive feedback between warming, the dominance of planktivorous fish populations, and bottom-up regulation caused predator-prey role reversal, and probably resulted in three regime shifts of Lake Hulun over 56 years. This study provides a comprehensive analysis of ecological regime shifts in Hulun Lake fish communities, and has potential implications for fish species living in similar environments that are subject to global warming, land-use changes, and overfishing.

Non-additive effects of foundation species determine the response of aquatic ecosystems to nutrient perturbation

Eutrophication is a persistent threat to aquatic ecosystems worldwide. Foundation species, namely those that play a central role in the structuring of communities and functioning of ecosystems, are likely important for the resilience of aquatic ecosystems in the face of disturbance. However, little is known about how interactions among such species influence ecosystem responses to nutrient perturbation. Here, using an array (N = 20) of outdoor experimental pond ecosystems (15,000 L), we manipulated the presence of two foundation species, the macrophyte Myriophyllum spicatum and the mussel Dreissena polymorpha, and quantified ecosystem responses to multiple nutrient disturbances, spread over two years. In the first year, we added five nutrient pulses, ramping up from 10 to 50 μg P/L over a 10-week period from mid-July to mid-October, and in the second year, we added a single large pulse of 50 μg P/L in mid-October. We used automated sondes to measure multiple ecosystems properties at high frequency (15-minute intervals), including phytoplankton and dissolved organic matter fluorescence, and to model whole-ecosystem metabolism. Overall, both foundation species strongly affected the ecosystem responses to nutrient perturbation, and, as expected, initially suppressed the increase in phytoplankton abundance following nutrient additions. However, when both species were present, phytoplankton biomass increased substantially relative to other treatment combinations: non-additivity was evident for multiple ecosystem metrics following the nutrient perturbations in both years but was diminished in the intervening months between our perturbations. Overall, these results demonstrate how interactions between foundation species can cause surprisingly strong deviations from the expected responses of aquatic ecosystems to perturbations such as nutrient additions.

Predicting ecosystem state changes in shallow lakes using an aquatic ecosystem model: Lake Hinge, Denmark, an example

In recent years, considerable efforts have been made to restore turbid, phytoplankton-dominated shallow lakes to a clear-water state with high coverage of submerged macrophytes. Various dynamic lake models with simplified physical representations of vertical gradients, such as PCLake, have been used to predict external nutrient load thresholds for such nonlinear regime shifts. However, recent observational studies have questioned the concept of regime shifts by emphasizing that gradual changes are more common than sudden shifts. We investigated if regime shifts would be more gradual if the models account for depth-dependent heterogeneity of the system by including the possibility of vertical gradients in the water column and sediment layers for the entire depth. Hence, bifurcation analysis was undertaken using the 1D hydrodynamic model GOTM, accounting for vertical gradients, coupled to the aquatic ecosystem model PCLake, which is implemented in the framework for aquatic biogeochemical modeling (FABM). First, the model was calibrated and validated against a comprehensive data set covering two consecutive 7-yr periods from Lake Hinge, a shallow, eutrophic Danish lake. The autocalibration program Auto-Calibration Python (ACPy) was applied to achieve a more comprehensive adjustment of model parameters. The model simulations showed excellent agreement with observed data for water temperature, total nitrogen, and nitrate and good agreement for ammonium, total phosphorus, phosphate, and chlorophyll a concentrations. Zooplankton and macrophyte coverage were adequately simulated for the purpose of this study, and in general the GOTM-FABM-PCLake model simulations performed well compared with other model studies. In contrast to previous model studies ignoring depth heterogeneity, our bifurcation analysis revealed that the spatial extent and depth limitation of macrophytes as well as phytoplankton chlorophyll-a responded more gradually over time to a reduction in the external phosphorus load, albeit some hysteresis effects still appeared. In a management perspective, our study emphasizes the need to include depth heterogeneity in the model structure to more correctly determine at which external nutrient load a given lake changes ecosystem state to a clear-water condition.

Interactive effects of foundation species on ecosystem functioning and stability in response to disturbance

A major challenge in ecology is to understand determinants of ecosystem functioning and stability in the face of disturbance. Some important species can strongly shape community structure and ecosystem functioning, but their impacts and interactions on ecosystem-level responses to disturbance are less well known. Shallow ponds provide a model system in which to study the effects of such species because some taxa mitigate transitions between alternative ecosystem states caused by eutrophication. We performed pond experiments to test how two foundation species (a macrophyte and a mussel) affected the biomass of planktonic primary producers and its stability in response to nutrient additions. Individually, each species reduced phytoplankton biomass and tended to increase rates of recovery from disturbance, but together the species reversed these effects, particularly with larger nutrient additions. This reversal was mediated by high cyanobacterial dominance of the community and a resulting loss of trait evenness. Effects of the foundation species on primary producer biomass were associated with effects on other ecosystem properties, including turbidity and dissolved oxygen. Our work highlights the important role of foundation species and their interactive effects in determining responses of ecosystem functioning to disturbance.

Time scale of resilience loss: Implications for managing critical transitions in water quality

Regime shifts involving critical transitions are a type of rapid ecological change that are difficult to predict, but may be preceded by decreases in resilience. Time series statistics like lag-1 autocorrelation may be useful for anticipating resilience declines; however, more study is needed to determine whether the dynamics of autocorrelation depend on the resolution of the time series being analyzed, i.e., whether they are time-scale dependent. Here, we examined timeseries simulated from a lake eutrophication model and gathered from field measurements. The field study involved collecting high frequency chlorophyll fluorescence data from an unmanipulated reference lake and a second lake undergoing experimental fertilization to induce a critical transition in the form of an algal bloom. As part of the experiment, the fertilization was halted in response to detected early warnings of the algal bloom identified by increased autocorrelation. We tested these datasets for time-scale dependence in the dynamics of lag-1 autocorrelation and found that in both the simulation and field experiment, the dynamics of autocorrelation were similar across time scales. In the simulated time series, autocorrelation increased exponentially approaching algal bloom development, and in the field experiment, the difference in autocorrelation between the manipulated and reference lakes increased sharply. These results suggest that, as an early warning indicator, autocorrelation may be robust to the time scale of the analysis. Given that a time scale can be shortened by increasing sampling frequency, or lengthened by aggregating data during analysis, these results have important implications for management as they demonstrate the potential for detecting early warning signals over a wide range of monitoring frequencies and without requiring analysts to make situation-specific decisions regarding aggregation. Such an outcome provides promise that data collection procedures, especially by automated sensors, may be used to monitor and manage ecosystem resilience without the need for strict attention to time scale.

Integrating long-term dynamics of ecosystem services into restoration and management of large shallow lakes

Adequately understanding the dynamics of ecosystem services (ES), a practical framework for analyzing social-ecological systems (SES), is crucial for sustainable environmental management and decision-making. However, the interactions among multiple ES at multi-decadal scales are less explored, and many challenges remain to integrate long-term dynamics of ES into ecological restoration and management. Here, we combined socioeconomic data with synthesized paleolimnological records to assess the dynamics of 12 critical ES and regional SES in the Taihu Lake Basin (China) over the past century. Our results indicated that multiple provisioning services showed upwards trends while major regulating services in terms of water, sediment, soil and air regulation had sustained downwards trends since the 1950s, and reached dangerous status after the 1980s. This dynamic trade-off was mainly attributed to the effects of continued socioeconomic transitions including agriculture intensification, industrialization and urbanization. Anthropogenic land use change, pollution input, and climate changes are considered as major drivers of long-term environmental degradation. Regulating services exhibited various dynamical properties including different linear and nonlinear trends, and abrupt changes, which underlined the comprehensive consideration of legacy effects, ecological baseline, thresholds, and resilience into lake management. Environmental Kuznets curve analyses suggested that the regional SES started significant disorder from the 1970s driven by the transition between ES and non-ES (socioeconomic) supply, and then underpinned a gradual shift to reorganization stage after the 1990s. Our study highlights the significance of ES assessment from historical perspective to understand the major processes and underlying mechanisms of lake SES. With adaptive policy interventions on pollution control, efficient resource-use, and targeted environmental investment, the sustainability of regional SES can be expected.